code: def test_correctness(self):
      sequence = (
          np.arange(120).reshape((2, 3, 4, 5)).astype("float32") / 10
      )
      expected_output = np.array(
          [
              [[0.40807986, 0.40807986], [0.46421072, 0.46421072]],
              [[0.80933154, 0.80933154], [0.8233646, 0.8233646]],
          ]
      )
      if backend.config.image_data_format() == "channels_first":
          sequence = sequence.transpose((0, 1, 3, 2))
          expected_output = expected_output.transpose((0, 2, 1))
      layer = layers.ConvLSTM1D(
          filters=2,
          kernel_size=3,
          kernel_initializer=initializers.Constant(0.01),
          recurrent_initializer=initializers.Constant(0.02),
          bias_initializer=initializers.Constant(0.03),
      )
      output = layer(sequence)
      self.assertAllClose(
          expected_output,
          output,
      )
  
file_path: keras/keras/layers/rnn/conv_lstm1d_test.py
imports: import numpy
  import pytest
  from keras import backend
  from keras import initializers
  from keras import layers
  from keras import testing
label_desc: Use image node_id 2 for calling the ConvLSTM1DTest obj's underlying member method code with example usage: obj.test_correctness() without return types